Search results

The internet is rapidly becoming the main channel for seeking and booking travel services. The consequent human–interface interactions are now the focal point of many studies being conducted by both scholars and practitioners. The development of websites involves many design choices, such as background, colors, fonts, and different ways of presenting information. The study here argues that these seemingly “trivial” design choices may have nontrivial effects on customers’ behavior. The study presents three empirical examples supporting this idea. The first example refers to the presentation of hotels as items on a list on websites, which creates a “mere position” effect. The second example shows that different partitioning of an attribute’s values can impact their relative importance. The third example shows that background features (color, picture) may result in priming effects. In all cases, the seemingly trivial changes in design directly alter customers’ choices although, rationally, they should have no impact at all.

This chapter explains and discusses the role and potential of psychophysiological tools of research in tourism and hospitality. As tourism and hospitality services are in general inseparable, i.e. the delivery and the consumption of the service mostly take place at the same time, they tend to involve service encounters which intense and frequent contact and social interactions between the customers and the service providers. These intense and frequent contact and social interactions during service encounters may determine the satisfaction and dissatisfaction of the customers. Hence, the measurement of actual emotions to understand the reactions of customers to various aspects of the service is of paramount importance. Psychophysiological tools, often referred to as neuromarketing tools, allow the collection of realistic data regarding the emotions of the customers. Based on the above background, this chapter explains and discusses the use of tools such as the EEG, Eye Tracker, Galvanic Skin Response, and Facial Expression Recognition in understanding tourism and hospitality customers' reactions and emotions to various aspects of the service.

Using data from securities analysts, who are awarded status by the third-party organization Institutional Investor magazine, we examine the emergence of competition and articulate a model of competitive response among actors aware of the importance of status and some of the dimensions on which it may be gained. We predict analysts’ initiating or ceasing coverage of stocks in response to other analysts initiating coverage on stocks they cover. We find that competition can emerge because of status seeking rather than as a response to own capabilities or market needs, with compelling, and potentially negative, market implications for overt status seeking.

Hotels, the second largest component of online travel, have traditionally collected customer data through loyalty or customer relationship management programmes, compiling data about customers and using it to improve customer service and marketing efforts (Piccoli & O’Connor, 2003). Recent growth in online sales has given them access to even more granular and topical data. In particular technologies such as cookies, web bugs and beacons allow data on an individual’s browsing (e.g. the pages they have visited or the searches they have conducted) to be collected, consolidated and analysed to reveal detailed insights about customers which can subsequently be used for marketing purposes (Gilbert, 2008). While previous studies have investigated data collection by hotels, for the most part these have focussed on data surrendered voluntarily, with none addressing data collection through automated means. This chapter therefore attempts to fill this research gap, investigating whether and how hotel companies use such techniques, and whether consumers are adequately informed about this data collection process. Using the top 50 global hotel brands as a population, it explores both cookie disclosure and cookie practice by global hotel brands. The findings demonstrate that hotel brands, particularly those with their headquarters in the USA, are making extensive use of online monitoring technologies, typically for marketing purposes. In most cases, this data collection is happening surreptitiously, with the data protection notices that exist overtly long as well as crouched in highly technical language. Despite legislative changes that amplify the need to inform consumers about data collection, few hotel chains currently comply with the principles of informed consent, leaving many open to potential sanction.

The discovery of internet technologies which is one of the most important developments of the twenty-first century has enabled individuals and institutions to overcome geographical and time constraints creating fundamental changes in communication. As a result, online communities have enabled people to meet the internet for various reasons such as seeking and sharing information, discuss community issues and ask questions; and online communities have also enabled businesses and consumers to connect with each other at any time. Especially the emergence of Internet-based social media technologies such as blogs, virtual communities, wikis, social networks, YouTube, Facebook and Instagram provides tourists to share their travel experiences. Information shared on social media sites is considered to be an important source of information that can help tourists’ travel plan and may even influence the travel decisions of potential tourists. In this context, the concept of social media in tourism businesses has been examined in the research. Within the framework of the research, it has been observed that social media has influenced the tourists’ behavior regarding travel motivations in the context of various motivations (having information about destinations, hotels, services of hotels, wondering about consumers’ experiences who were in touristic consumption before, etc.). It is also among other findings that social media has increased the overtourism crisis.

Budget hotels are becoming an emerging industry for convenience and affordability, where consumer sentiments are of paramount importance. Tourism has become increasingly dependent on social media and online platforms to gather travel-related information, purchase travel products, food, lodging, etc., and share views and experiences. The user-generated data helps companies make informed decisions through predictive and behavioural analytics.

Design/Methodology/Approach: This study uses text mining, deep learning, and machine learning techniques for data collection and sentiment analysis based on 117,151 online reviews of the customers posted on the TripAdvisor website from May 2004 to May 2019 from 197 hotels of five prominent budget hotel groups spread across India using Feedforward Neural Network along with Keras package and Softmax activation function.

Findings: The word-of-mouth turns into electronic word-of-mouth through social networking sites, with easy access to information that enables customers to pick a budget hotel. We identified 20 widely used words that most customers use in their reviews, which can help managers optimise operational efficiency by boosting consumer acceptability, satisfaction, positive experiences, and overcoming negative consumer perceptions.

Practical Implications: The analysis of the review patterns is based on real-time data, which is helpful to understand the customer’s requirements, particularly for budget hotels.

Originality/Value: We analysed TripAdvisor reviews posted over the last 16 years, excluding the Corona period due to industry crises. The findings reverberate in consonance with the performance improvement theory, which states feed-forward a neural network enhances organisational, process, and individual-level performance in the hospitality industry based on customer reviews.

The objective of this chapter is to establish the positioning on Booking.com of hotels located in the cities of Tehran, Kashan, Abyaneh, Isfahan, Yazd, Persepolis, and Shiraz, the main tourism destinations in the Islamic Republic of Iran. The methodology is quantitative, consisting of the development of a “Spyder” that allows content to be identified and timely information to be extracted from the web. The data obtained allow to establish the average rating by the evaluation categories stated by the platform, while contributing to determining the strengths and weaknesses that the establishments present. These relevant data can thus contribute to the improvement of the services and the destination in general.

Measuring and evaluating the effectiveness of a website can be very difficult and subjective. These sites can be evaluated in different ways, depending on which factor is considered as the most important one in promoting a website. Theory suggests some key factors when evaluating the effectiveness of a Web site, such as the quantity of information provided, the design of the Web site, or the reciprocity created with the customer. This chapter focuses on these factors to evaluate effectiveness. However, to complete this evaluation, it is highly recommended using other traditional tools like survey methodology. Both online and email surveys are necessary to get a more detailed conclusion when investigating effectiveness of a tourism promotional Web site. Evaluation of Web site effectiveness is necessary because of the significant costs for setup, advertising, and maintenance.